Plotly BioVisualization with Python

#️⃣ What is the purpose of this repo?

Tremendous advances in the field of biotechnology enable researchers and scientists to produce and obtain a diverse and huge amount of biological data. Therefore, there is a corresponding increase in the way of visualizing the biological data to represent information and science through art in a concise and meaningful way.

In this respect, Plotly has recently emerged and it can be used to create interactive charts and state-of-the-art graphs in a wide range of visualization applications including visualization of sequences, genomes, alignments, gene expressions.

So, I have wanted to learn how to use this library with Python, create some great charts and shared them.

#️⃣ How it looks like in general?

#️⃣ Requirements and Installation

Create a directory and download all files or clone the repository via Git using the following command:

git clone https://github.com/furkanmtorun/Plotly_BioVisualization.git
Install the required packages if you do not already:

pip install -r requirements.txt
Then, the turn to run it:

python Plotly_BioVisualization.py
It's ready to use now! Open your web browser and go to:

http://127.0.0.1:8050

If you did not install pip yet, please follow the instruction here.

In the development process, Python 3 has been used. The use of Python 2.x might cause compatibility issues.

#️⃣ How to create interactive graphs and charts?

#️⃣ Needle Plot
- Purpose: It allows you to illustrate the mutations or other changes on the corresponding positions of amino acids within the protein sequence together with the protein domains.
- Data structure: JSON / Dict = { x: [], y: [], domains: [], mutationGroups: [] }
- Coding (just review the code, the comments are over there!):
- How it looks like?:
#️⃣ Sequence/Alignment Viewer
- Purpose: It allows you to visualize the genomics and transcriptomic sequence with several features such as coverage, gaps, consensus, and heatmap overview.
- Data Structure: FASTA / Clustal
- Coding (just review the code, the comments are over there!):
- How it looks like?
#️⃣ Manhattan Plot
- Purpose: Manhattan Plot is a type of scatter plot and commonly used in genome-wide association studies (GWAS) to visualize display significant SNPs efficiently.
  
  The genome-wide significance threshold was set as 5e-8 and plotted with green line, and the most significant SNPs are colored in red.
- Coding (just review the code, the comments are over there!):
- How it looks like?